WO2017041730A1 - Method and system for navigating mobile robot to bypass obstacle - Google Patents

Method and system for navigating mobile robot to bypass obstacle Download PDF

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WO2017041730A1
WO2017041730A1 PCT/CN2016/098460 CN2016098460W WO2017041730A1 WO 2017041730 A1 WO2017041730 A1 WO 2017041730A1 CN 2016098460 W CN2016098460 W CN 2016098460W WO 2017041730 A1 WO2017041730 A1 WO 2017041730A1
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robot
node
execute
obstacle
movement
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王玉亮
王晓刚
王巍
薛林
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北京进化者机器人科技有限公司
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    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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    • G05D1/02—Control of position or course in two dimensions

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Abstract

A method for navigating a mobile robot to bypass an obstacle. The method comprises: establishing a global map (101); setting a starting point and a finishing point (102); planning a path according to an A* algorithm (103); detecting the position of an obstacle (104); replanning the path according to the A* algorithm (105); controlling a robot to move (106); determining whether the robot reaches the finishing point (107); and stopping moving (108).Also provided is a system for navigating a mobile robot to bypass an obstacle.The present invention ensures the accuracy and effectiveness of navigating a robot to bypass an obstacle.

Description

一种移动机器人避障导航的方法和系统Method and system for obstacle avoidance navigation of mobile robot 技术领域Technical field
本发明涉及自动化技术领域，特别涉及一种移动机器人避障导航的方法和系统。The present invention relates to the field of automation technologies, and in particular, to a method and system for obstacle avoidance navigation of a mobile robot.
背景技术Background technique
机器人技术的发展是科学技术综合发展的共同结晶。机器人按照用途可以分为军用机器人、工业机器人、服务机器人等，其中，这些机器人类型中都对移动机器人有巨大的需求。The development of robotics is the common crystallization of the comprehensive development of science and technology. According to the purpose, the robot can be divided into military robots, industrial robots, service robots, etc. Among them, there are huge demands for mobile robots among these robot types.
移动机器人的研究范围涵盖：体系结构、控制机构、信息系统、传感技术、规划策略、以及驱动系统等几个方面，涉及机械运动学、人工智能、智能控制、模式识别、图像处理、视觉技术、传感技术、计算机网络与通讯、以至生物信息技术等在内的多个学科领域。移动机器人不仅在工业、农业、医疗、服务等行业中得到广泛的应用，而且在城市安全、国防和空间探测领域等有害与危险场合得到很好的应用。移动机器人的研究水平，是衡量一个国家科技发展水平和综合国力的重要标志。“机器人革命”有望成为“第三次工业革命”的一个切入点和重要增长点，将影响全球制造业格局。国际机器人联合会(IFR)预测：“机器人革命”将创造数万亿美元的市场，从而带动与机器人相关的新材料功能模块、感知获取与识别、智能控制与导航等关键技术与市场快速发展。The research scope of mobile robots covers architecture, control mechanism, information system, sensing technology, planning strategy, and drive system, including mechanical kinematics, artificial intelligence, intelligent control, pattern recognition, image processing, and visual technology. , a variety of subject areas such as sensor technology, computer networks and communications, and even bioinformatics. Mobile robots are widely used not only in industries such as industry, agriculture, medical care, and services, but also in hazardous and dangerous environments such as urban security, defense, and space exploration. The research level of mobile robots is an important indicator to measure a country's level of scientific and technological development and comprehensive national strength. The "robot revolution" is expected to be an entry point and an important growth point for the "third industrial revolution", which will affect the global manufacturing landscape. The International Federation of Robotics (IFR) predicts that the "robot revolution" will create a trillion-dollar market, leading to the rapid development of key technologies and markets such as new material functional modules related to robots, sensory acquisition and recognition, intelligent control and navigation.
智能机器人，如，扫地机器人、家庭服务机器人越来越广泛地应用于工业生产和家庭生活中，机器人要实现灵活、高效、智能地移动，需要具有自主导航能力。自主避障技术是评价机器人智能化程度的关键指标，体现了对未知障碍物的处理能力，也是智能机器人在位置环境下完成预设任务的关键技术之 一。移动机器人处在未知、复杂、动态的非结构化环境中，在没有人工干预的条件下，应该具备利用自身携带的传感器感知其所处环境信息的能力，并对环境进行建模，能够自主避开障碍物，同时尽量减少时间和能量的消耗。Intelligent robots, such as sweeping robots and home service robots, are increasingly used in industrial production and family life. Robots need to have autonomous navigation capabilities to achieve flexible, efficient, and intelligent movement. Autonomous obstacle avoidance technology is a key indicator for evaluating the intelligence degree of robots, which reflects the ability to deal with unknown obstacles. It is also the key technology for intelligent robots to complete preset tasks in the location environment. One. The mobile robot is in an unknown, complex and dynamic unstructured environment. Without human intervention, it should have the ability to use its own sensors to sense the information about its environment, and model the environment. Open obstacles while minimizing time and energy consumption.
在机器人避障导航技术领域，国内外学者都提出了有效的解决方案。通过超声波传感器探测障碍物，利用指南针定位，辅以贝叶斯概率算法计算障碍物占据的概率，从而实现环境信息监测和路径规划。最优控制技术利用视觉反馈来解决机器人的避障问题，利用和机器人期望行为相关的基于图像目标图像最小方案来控制机器人，利用动态拟牛顿法来进行动态递归最小二乘Jacobian估计来实现目标函数的最小化。通过利用单目摄像机来获取障碍物的大致三维信息，利用超声波传感器来获取障碍物的精确信息，利用单目视觉和超声波共同探测障碍物信息。中国科学院开发的智能移动机器人平台——爱姆，具有视觉跟踪、语音对话、自主避障等综合功能，安装有16个超声波传感器和16个红外传感器来探测障碍物。In the field of robotic obstacle avoidance navigation technology, domestic and foreign scholars have proposed effective solutions. Ultrasonic sensors are used to detect obstacles, using compass positioning, and Bayesian probability algorithm to calculate the probability of obstacle occupancy, thus achieving environmental information monitoring and path planning. The optimal control technology uses visual feedback to solve the obstacle avoidance problem of the robot. The robot based on the image target image minimum scheme is used to control the robot. The dynamic quasi-Newton method is used to perform dynamic recursive least square Jacobian estimation to achieve the objective function. Minimize. By using a monocular camera to obtain the approximate three-dimensional information of the obstacle, the ultrasonic sensor is used to acquire accurate information of the obstacle, and the monocular vision and the ultrasonic wave are used together to detect the obstacle information. The intelligent mobile robot platform developed by the Chinese Academy of Sciences - Aim, has comprehensive functions such as visual tracking, voice dialogue, and autonomous obstacle avoidance. It is equipped with 16 ultrasonic sensors and 16 infrared sensors to detect obstacles.
现有的机器人自主避障导航技术，多存在结构复杂、硬件成本昂贵、维护成本高的缺点，不适应快速增长的机器人发展需求。The existing robotic autonomous obstacle avoidance navigation technology has many shortcomings such as complicated structure, high hardware cost and high maintenance cost, and is not suitable for the rapid development of robot development.
发明内容Summary of the invention
本发明提供一种移动机器人避障导航的方法和系统，能够对未知的环境进行探测，获取不明障碍物的信息，并引入估计函数来规划最短、最经济的路径，节约了机器人避障导航的设备成本。本方案还能够实时监测机器人的位置和移动姿态，根据机器人和规划路径的偏差来实时、动态的调整和控制机器人的行走状态，保证了机器人避障导航的准确性和有效性。The invention provides a method and a system for obstacle avoidance navigation of a mobile robot, which can detect an unknown environment, acquire information of unknown obstacles, and introduce an estimation function to plan the shortest and most economical path, thereby saving robot obstacle avoidance navigation. Equipment cost. The program can also monitor the position and moving posture of the robot in real time, and adjust and control the walking state of the robot in real time and dynamically according to the deviation of the robot and the planning path, thus ensuring the accuracy and effectiveness of the obstacle avoidance navigation of the robot.
本发明的技术方案提供了一种移动机器人避障导航的方法，包括以下步骤：The technical solution of the present invention provides a method for obstacle avoidance navigation of a mobile robot, comprising the following steps:
建立家庭环境的全局地图；Establish a global map of the home environment;
设置机器人移动的起点和终点； Set the start and end points of the robot movement;
根据A*算法规划机器人的移动路径；Plan the moving path of the robot according to the A* algorithm;
在所述全局地图中标记障碍物的位置；Marking the location of the obstacle in the global map;
根据A*算法重新规划机器人的移动路径；Re-planning the movement path of the robot according to the A* algorithm;
根据所述规划的路径控制机器人移动；Controlling robot movement according to the planned path;
机器人到达终点，则停止移动。When the robot reaches the end, it stops moving.
进一步的，A*算法包括下述步骤：Further, the A* algorithm includes the following steps:
A、把起点s放入open表；A, put the starting point s into the open table;
B、遍历s节点周围8个方向的子节点；B. Traversing the child nodes in eight directions around the s node;
C、判断8个子节点是否在open表或close表中；C. Determine whether the eight child nodes are in the open table or the close table;
若子节点在open表，执行D；If the child node is in the open table, execute D;
若子节点在close表，执行F；If the child node is in the close table, execute F;
若子节点不在open表或close表，执行H；If the child node is not in the open or close table, execute H;
D、重新计算open表中节点h(n)+g(n)值，并判断是否减小；D. Recalculate the value of the node h(n)+g(n) in the open table, and determine whether to decrease;
若减小，则执行E；If it decreases, execute E;
若未发生减小，则执行I；If no reduction occurs, execute I;
E、更新open表中节点的h(n)+g(n)值，转向I；E, update the h(n)+g(n) value of the node in the open table, and turn to I;
F、重新计算close表中节点的h(n)+g(n)值，并判断是否减小；F. Recalculate the h(n)+g(n) values of the nodes in the close table, and determine whether to decrease;
若减小，则执行G；If it is decreased, execute G;
若未发生减小，则执行I；If no reduction occurs, execute I;
G、该子节点从close表移出，放到open表，转向I；G, the child node is removed from the close table, placed in the open table, and turned to I;
H、计算该子节点h(n)+g(n)值，并将其加入open表；H. Calculate the value of the child node h(n)+g(n) and add it to the open table;
I、按照h(n)+g(n)的值进行排序，选择该值最小的节点放入close表；I, sort according to the value of h (n) + g (n), select the node with the smallest value into the close table;
J、判断h(n)是否为0；J. Determine whether h(n) is 0;
若为0，则执行K；If it is 0, execute K;
若不为0，则执行B；If not 0, execute B;
K、找到终点。 K, find the end.
其中，open表用于存放已经生成而未考察的节点；The open table is used to store nodes that have been generated but not examined;
closed表用于记录已经访问过的节点。The closed table is used to record nodes that have already been visited.
进一步的，所述f(n)值的计算方法为：Further, the calculation method of the f(n) value is:
节点n的相邻节点有八个搜索方向，分别为上、下、左、右、左上、左下、右上和右下；The adjacent nodes of node n have eight search directions, namely upper, lower, left, right, upper left, lower left, upper right, and lower right;
对每个搜索方向，均使用估计函数来计算从当前点到下一个点的估计值，将估计值最小的方向置为下一个运动方向。For each search direction, an estimation function is used to calculate an estimate from the current point to the next point, and the direction in which the estimate is minimized is set to the next direction of motion.
进一步的，所述估计函数为Further, the estimation function is
f(n)＝g(n)+h(n)f(n)=g(n)+h(n)
其中，among them,
f(n)为当前点到下一点的估计值，f(n) is the estimated value from the current point to the next point.
g(n)为从起点s到节点n之间的实际值，代表了搜索广度的优先趋势，g(n) is the actual value from the starting point s to the node n, representing the priority trend of the search breadth.
h(n)为从节点n到目标点D之间的最佳路径的估计值，包含了搜索中的启发信息。h(n) is an estimate of the best path from node n to target point D, containing heuristic information in the search.
进一步的，使用超声波检测障碍物，并将障碍物在机器人坐标系下的位置转换为全局地图中的位置；Further, the obstacle is detected using ultrasonic waves, and the position of the obstacle in the robot coordinate system is converted into a position in the global map;
设定障碍物检测阈值为1500mm，超过1500mm不做处理，小于1500mm则将障碍物在全局地图中标记。Set the obstacle detection threshold to 1500mm, do not process more than 1500mm, and mark obstacles in the global map if it is less than 1500mm.
进一步的，规划出的路径用二维数组表示；Further, the planned path is represented by a two-dimensional array;
所述二维数组的行数表示路径中直线段的个数，列数表示每个直线段中的栅格位置；The number of rows of the two-dimensional array represents the number of straight segments in the path, and the number of columns represents the position of the grid in each straight segment;
所述二维数组所定义的路径中的点为局部目标点。The point in the path defined by the two-dimensional array is a local target point.
进一步的，所述根据所述规划的路径控制机器人移动，进一步包括：Further, the controlling the movement of the robot according to the planned path further includes:
在运动过程中实时更新机器人的位置和姿态；Updating the position and posture of the robot in real time during the movement;
计算机器人当前位置与所述局部目标点的偏差，在行走过程中实时纠正偏差，实现机器人的实时控制。 Calculate the deviation between the current position of the robot and the local target point, correct the deviation in real time during the walking process, and realize real-time control of the robot.
本发明的技术方案还提供了一种移动机器人避障导航的系统，包括：控制单元、里程计、超声波传感器、姿态传感器，其中，The technical solution of the present invention further provides a system for obstacle avoidance navigation of a mobile robot, comprising: a control unit, an odometer, an ultrasonic sensor, and an attitude sensor, wherein
控制单元用于存储和调整地图，计算A*算法，控制机器人移动，纠正机器人移动的偏差；The control unit is used to store and adjust the map, calculate the A* algorithm, control the movement of the robot, and correct the deviation of the robot movement;
里程计用于测量机器人在室内行走的距离；The odometer is used to measure the distance the robot walks indoors;
超声波传感器用于探测机器人周围的障碍物信息；An ultrasonic sensor is used to detect obstacle information around the robot;
姿态传感器用于探测机器人的姿态和移动方向。The attitude sensor is used to detect the attitude and direction of movement of the robot.
进一步的，控制单元接收来自里程计的测量数据，计算机器人的位置；Further, the control unit receives the measurement data from the odometer and calculates the position of the robot;
控制单元根据机器人所处的位置，计算与规划路径中的局部目标点的偏差。The control unit calculates a deviation from the local target point in the planned path according to the position of the robot.
进一步的，控制单元接收姿态传感器的测量数据，获得机器人的姿态和移动方向；Further, the control unit receives the measurement data of the attitude sensor to obtain the posture and the moving direction of the robot;
控制单元根据计算出的所述偏差和机器人的姿态，实时控制机器人的运动。The control unit controls the motion of the robot in real time based on the calculated deviation and the posture of the robot.
本发明技术方案提供一种移动机器人避障导航的方法和系统，能够对未知的环境进行探测，获取不明障碍物的信息，并采用估计函数来规划最短、最经济的路径，节约了机器人避障导航系统的设备成本。本方案还能够实时监测机器人的位置和移动姿态，根据机器人和规划路径的偏差来实时、动态的调整和控制机器人的行走状态，保证了机器人避障导航的准确性和有效性。The technical solution of the present invention provides a method and system for obstacle avoidance navigation of a mobile robot, which can detect an unknown environment, acquire information of unknown obstacles, and use an estimation function to plan the shortest and most economical path, thereby saving robot obstacle avoidance. Equipment cost of the navigation system. The program can also monitor the position and moving posture of the robot in real time, and adjust and control the walking state of the robot in real time and dynamically according to the deviation of the robot and the planning path, thus ensuring the accuracy and effectiveness of the obstacle avoidance navigation of the robot.
本发明的其它特征和优点将在随后的说明书中阐述，并且，部分地从说明书中变得显而易见，或者通过实施本发明而了解。本发明的目的和其他优点可通过在所写的说明书、权利要求书、以及附图中所特别指出的结构来实现和获得。Other features and advantages of the invention will be set forth in the description which follows, The objectives and other advantages of the invention may be realized and obtained by means of the structure particularly pointed in the appended claims.
下面通过附图和实施例，对本发明的技术方案做进一步的详细描述。 The technical solution of the present invention will be further described in detail below through the accompanying drawings and embodiments.
附图说明DRAWINGS
附图用来提供对本发明的进一步理解，并且构成说明书的一部分，与本发明的实施例一起用于解释本发明，并不构成对本发明的限制。在附图中：The drawings are intended to provide a further understanding of the invention, and are intended to be a In the drawing:
图1为本发明实施例一中移动机器人避障导航的方法流程图；1 is a flowchart of a method for obstacle avoidance navigation of a mobile robot according to Embodiment 1 of the present invention;
图2为本发明实施例一中估计函数f(n)的计算示意图；2 is a schematic diagram of calculation of an estimation function f(n) according to Embodiment 1 of the present invention;
图3为本发明实施例一中节点a相邻的8个搜索方向示意图；3 is a schematic diagram of eight search directions adjacent to node a in the first embodiment of the present invention;
图4为本发明实施例二中根据A*算法规划机器人的移动路径的方法流程图；4 is a flowchart of a method for planning a moving path of a robot according to an A* algorithm according to Embodiment 2 of the present invention;
图5为本发明实施例一至二中移动机器人避障导航系统的结构图。FIG. 5 is a structural diagram of a mobile robot obstacle avoidance navigation system according to Embodiments 1 to 2 of the present invention.
具体实施方式detailed description
以下结合附图对本发明的优选实施例进行说明，应当理解，此处所描述的优选实施例仅用于说明和解释本发明，并不用于限定本发明。The preferred embodiments of the present invention are described with reference to the accompanying drawings, which are intended to illustrate and illustrate the invention.
实施例一：移动机器人避障导航的方法。Embodiment 1: A method for mobile robot obstacle avoidance navigation.
图1为本发明实施例一中移动机器人避障导航的方法流程图。如图1所示，该流程包括以下步骤：FIG. 1 is a flowchart of a method for obstacle avoidance navigation of a mobile robot according to Embodiment 1 of the present invention. As shown in Figure 1, the process includes the following steps:
步骤101、建立家庭环境的全局地图。Step 101: Establish a global map of the home environment.
全局地图为机器人所处活动范围，标识有坐标原点、障碍物、活动范围等信息；The global map is the range of activities in which the robot is located, and the information such as the origin of the coordinates, obstacles, and range of activities are identified;
全局地图为栅格地图，由一系列正方形栅格组成的网状图形，标记室内环境的信息；The global map is a grid map, a network of graphs consisting of a series of square grids that mark information about the indoor environment;
栅格地图以横坐标(X坐标)和纵坐标(Y坐标)记录栅格的位置，以CV值来记录每个栅格被障碍物所占据的概率。The raster map records the position of the grid in abscissa (X coordinates) and ordinate (Y coordinates), and records the probability that each grid is occupied by obstacles by CV value.
步骤102、设置机器人移动的起点和终点。Step 102: Set a starting point and an ending point of the robot movement.
通过人工输入机器人移动的起点和终点，或者为机器人的固定任务设置起 点和终点，或者通过语音识别为机器人布置起点和终点；Manually enter the start and end points of the robot movement, or set the robot's fixed task Point and end point, or arrange the start and end points for the robot through speech recognition;
机器人启动该任务，即从起点移动到终点。The robot initiates the task, moving from the starting point to the end point.
步骤103、根据A*算法规划机器人的移动路径。Step 103: Plan a moving path of the robot according to the A* algorithm.
A*算法包括下述步骤：The A* algorithm includes the following steps:
A、把起点s放入open表；A, put the starting point s into the open table;
B、遍历s节点周围8个方向的子节点；B. Traversing the child nodes in eight directions around the s node;
C、判断8个子节点是否在open表或close表中；C. Determine whether the eight child nodes are in the open table or the close table;
若子节点在open表，执行D；If the child node is in the open table, execute D;
若子节点在close表，执行F；If the child node is in the close table, execute F;
若子节点不在open表或close表，执行H；If the child node is not in the open or close table, execute H;
D、重新计算h(n)+g(n)，并判断是否减小；D. Recalculate h(n)+g(n) and judge whether it is reduced;
若减小，则执行E；If it decreases, execute E;
若未发生减小，则执行I；If no reduction occurs, execute I;
E、更新open表中节点的h(n)+g(n)值，转向I；E, update the h(n)+g(n) value of the node in the open table, and turn to I;
F、重新计算close表中节点的h(n)+g(n)值，并判断是否减小；F. Recalculate the h(n)+g(n) values of the nodes in the close table, and determine whether to decrease;
若减小，则执行G；If it is decreased, execute G;
若未发生减小，则执行I；If no reduction occurs, execute I;
G、该子节点从close表移出，放到open表，转向I；G, the child node is removed from the close table, placed in the open table, and turned to I;
H、计算该子节点h(n)+g(n)值，并将其加入open表；H. Calculate the value of the child node h(n)+g(n) and add it to the open table;
I、按照h(n)+g(n)的值进行排序，选择该值最小的节点放入close表；I, sort according to the value of h (n) + g (n), select the node with the smallest value into the close table;
J、判断h(n)是否为0；J. Determine whether h(n) is 0;
若为0，则执行K；If it is 0, execute K;
若不为0，则执行B；If not 0, execute B;
K、找到终点。K, find the end.
其中，open表用于存放已经生成而未考察的节点；The open table is used to store nodes that have been generated but not examined;
closed表用于记录已经访问过的节点。 The closed table is used to record nodes that have already been visited.
其中，估计函数f(n)值的计算方法为：Wherein, the calculation method of the estimated function f(n) value is:
节点n的相邻节点有八个搜索方向，分别为上、下、左、右、左上、左下、右上和右下；The adjacent nodes of node n have eight search directions, namely upper, lower, left, right, upper left, lower left, upper right, and lower right;
对每个搜索方向，均使用估计函数来计算从当前点到下一个点的估计值，将估计值最小的方向置为下一个运动方向；For each search direction, an estimation function is used to calculate an estimate from the current point to the next point, and the direction in which the estimate is minimized is set to the next direction of motion;
节点n的估计值为The estimated value of node n is
f(n)＝g(n)+h(n)f(n)=g(n)+h(n)
其中，among them,
f(n)为当前点到下一点的估计值，f(n) is the estimated value from the current point to the next point.
g(n)为从起点s到节点n之间的实际值，代表了搜索广度的优先趋势，g(n) is the actual value from the starting point s to the node n, representing the priority trend of the search breadth.
h(n)为从节点n到目标点D之间的最佳路径的估计值，包含了搜索中的启发信息。h(n) is an estimate of the best path from node n to target point D, containing heuristic information in the search.
规划出的路径用二维数组表示；The planned path is represented by a two-dimensional array;
所述二维数组的行数表示路径中直线段的个数，列数表示每个直线段中的栅格位置；The number of rows of the two-dimensional array represents the number of straight segments in the path, and the number of columns represents the position of the grid in each straight segment;
所述二维数组所定义的路径中的点为局部目标点。The point in the path defined by the two-dimensional array is a local target point.
步骤104、在移动过程中探测和标记障碍物的位置。Step 104: Detect and mark the location of the obstacle during the movement.
机器人在移动过程中，使用超声波探测障碍物的信息，并把障碍物在机器人坐标中的位置转化为在全局地图中的位置；During the movement of the robot, the ultrasonic is used to detect the obstacle information, and the position of the obstacle in the robot coordinates is converted into a position in the global map;
设定障碍物检测阈值为1500mm，超过1500mm不做处理，小于1500mm则将障碍物在全局地图中标记。Set the obstacle detection threshold to 1500mm, do not process more than 1500mm, and mark obstacles in the global map if it is less than 1500mm.
步骤105、根据A*算法重新规划机器人的移动路径。Step 105: Re-plan the moving path of the robot according to the A* algorithm.
根据添加障碍物信息的全局地图，重新根据A*算法来规划机器人的移动路径；According to the global map with the obstacle information added, the moving path of the robot is re-planned according to the A* algorithm;
机器人重新获得调整后的二维数组来表示新的路径。The robot regains the adjusted two-dimensional array to represent the new path.
步骤106、根据所述规划的路径控制机器人移动。 Step 106: Control robot movement according to the planned path.
通过行程计和姿态传感器，在运动过程中实时更新机器人的位置和姿态信息；The position and attitude information of the robot is updated in real time during the movement through the travel meter and the attitude sensor;
计算机器人当前位置与所述局部目标点的偏差，在行走过程中实时纠正偏差，实现机器人的实时控制。Calculate the deviation between the current position of the robot and the local target point, correct the deviation in real time during the walking process, and realize real-time control of the robot.
步骤107、判断机器人是否到达终点。Step 107: Determine whether the robot reaches the end point.
判断机器人的位置和终点是否重合Determine if the position and end point of the robot coincide
步骤108、机器人停止移动。In step 108, the robot stops moving.
机器人到达终点，即停止移动。When the robot reaches the end, it stops moving.
实施例二：根据A*算法规划机器人的移动路径的方法。Embodiment 2: A method of planning a moving path of a robot according to an A* algorithm.
图4为本发明实施例二中根据A*算法规划机器人的移动路径的方法流程图。如图4所示，该方法流程包括如下步骤：FIG. 4 is a flowchart of a method for planning a moving path of a robot according to an A* algorithm according to Embodiment 2 of the present invention. As shown in FIG. 4, the method process includes the following steps:
步骤201、把起点s放入open表；Step 201: Put the starting point s into the open table;
步骤202、遍历s节点周围8个方向的子节点；Step 202: Traversing child nodes in eight directions around the s node;
步骤203、判断8个子节点是否在open表或close表中；Step 203: Determine whether the eight child nodes are in an open table or a close table.
若子节点在open表，执行步骤204；If the child node is in the open table, step 204 is performed;
若子节点在close表，执行步骤206；If the child node is in the close table, step 206 is performed;
若子节点不在open表或close表，执行步骤208；If the child node is not in the open table or the close table, step 208 is performed;
步骤204、重新计算open表中节点h(n)+g(n)值，并判断是否减小；Step 204: Recalculate the value of the node h(n)+g(n) in the open table, and determine whether to decrease;
若减小，则执行步骤205；If the decrease, step 205 is performed;
若未发生减小，则执行步骤209；If no reduction occurs, step 209 is performed;
步骤205、更新open表中节点的h(n)+g(n)值，转向步骤209； Step 205, update the h (n) + g (n) value of the node in the open table, and proceeds to step 209;
步骤206、重新计算close表中节点的h(n)+g(n)值，并判断是否减小； Step 206, recalculating the value of h(n)+g(n) of the node in the close table, and determining whether to decrease;
若减小，则执行步骤207；If the decrease, step 207 is performed;
若未发生减小，则执行步骤209；If no reduction occurs, step 209 is performed;
步骤207、该子节点从close表移出，放到open表，转向步骤209； Step 207, the child node is removed from the close table, placed in the open table, and proceeds to step 209;
步骤208、计算该子节点h(n)+g(n)值，并将其加入open表；Step 208: Calculate the value of the child node h(n)+g(n) and add it to the open table.
步骤209、按照h(n)+g(n)的值进行排序，选择该值最小的节点放入close表；Step 209: Sort according to the value of h(n)+g(n), and select the node with the smallest value to be placed in the close table;
步骤210、判断h(n)是否为0；Step 210: Determine whether h(n) is 0;
若为0，则执行步骤211；If it is 0, then step 211 is performed;
若不为0，则执行步骤202；If not 0, step 202 is performed;
步骤211、找到终点。 Step 211, find the end point.
其中，open表用于存放已经生成而未考察的节点；The open table is used to store nodes that have been generated but not examined;
closed表用于记录已经访问过的节点。The closed table is used to record nodes that have already been visited.
图5为本发明实施例一至二中移动机器人避障导航系统的结构图。该系统包括：控制单元301、里程计302、超声波传感器303、姿态传感器304，其中，FIG. 5 is a structural diagram of a mobile robot obstacle avoidance navigation system according to Embodiments 1 to 2 of the present invention. The system includes: a control unit 301, an odometer 302, an ultrasonic sensor 303, and an attitude sensor 304, wherein
控制单元用于存储和调整地图，计算A*算法，控制机器人移动，纠正机器人移动的偏差；The control unit is used to store and adjust the map, calculate the A* algorithm, control the movement of the robot, and correct the deviation of the robot movement;
里程计用于测量机器人在室内行走的距离；The odometer is used to measure the distance the robot walks indoors;
超声波传感器用于探测机器人周围的障碍物信息；An ultrasonic sensor is used to detect obstacle information around the robot;
姿态传感器用于探测机器人的姿态和移动方向。The attitude sensor is used to detect the attitude and direction of movement of the robot.
进一步的，控制单元接收来自里程计的测量数据，计算机器人的位置；Further, the control unit receives the measurement data from the odometer and calculates the position of the robot;
控制单元根据机器人所处的位置，计算与规划路径中的局部目标点的偏差。The control unit calculates a deviation from the local target point in the planned path according to the position of the robot.
进一步的，控制单元接收姿态传感器的测量数据，获得机器人的姿态和移动方向；Further, the control unit receives the measurement data of the attitude sensor to obtain the posture and the moving direction of the robot;
控制单元根据计算出的所述偏差和机器人的姿态，实时控制机器人的运动。The control unit controls the motion of the robot in real time based on the calculated deviation and the posture of the robot.
本发明技术方案提供一种移动机器人避障导航的方法和系统，能够对未知 的环境进行探测，获取不明障碍物的信息，并引入估计函数来规划最短、最经济的路径，节约了机器人避障导航的设备成本。本方案还能够实时监测机器人的位置和移动姿态，根据机器人和规划路径的偏差来实时、动态的调整和控制机器人的行走状态，保证了机器人避障导航的准确性和有效性。The technical solution of the present invention provides a method and system for obstacle avoidance navigation of a mobile robot, which can The environment is detected, the information of unknown obstacles is obtained, and the estimation function is introduced to plan the shortest and most economical path, which saves the equipment cost of robot obstacle avoidance navigation. The program can also monitor the position and moving posture of the robot in real time, and adjust and control the walking state of the robot in real time and dynamically according to the deviation of the robot and the planning path, thus ensuring the accuracy and effectiveness of the obstacle avoidance navigation of the robot.
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器和光学存储器等)上实施的计算机程序产品的形式。Those skilled in the art will appreciate that embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) including computer usable program code.
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (system), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。The computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device. The apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device. The instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及 其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。 It is apparent that those skilled in the art can make various modifications and variations to the invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the invention are within the scope of the invention The invention is also intended to cover such modifications and variations within the scope of the equivalents.

Claims (10)

  1. 一种移动机器人避障导航的方法，其特征在于，包括以下步骤：A method for obstacle avoidance navigation of a mobile robot, comprising the steps of:
    建立家庭环境的全局地图；Establish a global map of the home environment;
    设置机器人移动的起点和终点；Set the start and end points of the robot movement;
    根据A*算法规划机器人的移动路径；Plan the moving path of the robot according to the A* algorithm;
    在所述全局地图中标记障碍物的位置；Marking the location of the obstacle in the global map;
    根据A*算法重新规划机器人的移动路径；Re-planning the movement path of the robot according to the A* algorithm;
    根据所述规划的路径控制机器人移动；Controlling robot movement according to the planned path;
    机器人到达终点，则停止移动。When the robot reaches the end, it stops moving.
  2. 根据权利要求1所述的方法，其特征在于，A*算法包括下述步骤：The method of claim 1 wherein the A* algorithm comprises the steps of:
    A、把起点s放入open表；A, put the starting point s into the open table;
    B、遍历s节点周围8个方向的子节点；B. Traversing the child nodes in eight directions around the s node;
    C、判断8个子节点是否在open表或close表中；C. Determine whether the eight child nodes are in the open table or the close table;
    若子节点在open表，执行D；If the child node is in the open table, execute D;
    若子节点在close表，执行F；If the child node is in the close table, execute F;
    若子节点不在open表或close表，执行H；If the child node is not in the open or close table, execute H;
    D、重新计算open表中节点h(n)+g(n)值，并判断是否减小；D. Recalculate the value of the node h(n)+g(n) in the open table, and determine whether to decrease;
    若减小，则执行E；If it decreases, execute E;
    若未发生减小，则执行I；If no reduction occurs, execute I;
    E、更新open表中节点的h(n)+g(n)值，转向I；E, update the h(n)+g(n) value of the node in the open table, and turn to I;
    F、重新计算close表中节点的h(n)+g(n)值，并判断是否减小；F. Recalculate the h(n)+g(n) values of the nodes in the close table, and determine whether to decrease;
    若减小，则执行G；If it is decreased, execute G;
    若未发生减小，则执行I；If no reduction occurs, execute I;
    G、该子节点从close表移出，放到open表，转向I；G, the child node is removed from the close table, placed in the open table, and turned to I;
    H、计算该子节点h(n)+g(n)值，并将其加入open表； H. Calculate the value of the child node h(n)+g(n) and add it to the open table;
    I、按照h(n)+g(n)的值进行排序，选择该值最小的节点放入close表；I, sort according to the value of h (n) + g (n), select the node with the smallest value into the close table;
    J、判断h(n)是否为0；J. Determine whether h(n) is 0;
    若为0，则执行K；If it is 0, execute K;
    若不为0，则执行B；If not 0, execute B;
    K、找到终点。K, find the end.
    其中，open表用于存放已经生成而未考察的节点；The open table is used to store nodes that have been generated but not examined;
    closed表用于记录已经访问过的节点。The closed table is used to record nodes that have already been visited.
  3. 根据权利要求1或2所述的方法，其特征在于，所述f(n)值的计算方法为：The method according to claim 1 or 2, wherein the calculation method of the f(n) value is:
    节点n的相邻节点有八个搜索方向，分别为上、下、左、右、左上、左下、右上和右下；The adjacent nodes of node n have eight search directions, namely upper, lower, left, right, upper left, lower left, upper right, and lower right;
    对每个搜索方向，均使用估计函数来计算从当前点到下一个点的估计值，将估计值最小的方向置为下一个运动方向。For each search direction, an estimation function is used to calculate an estimate from the current point to the next point, and the direction in which the estimate is minimized is set to the next direction of motion.
  4. 根据权利要求1或4所述的方法，其特征在于，所述估计函数为The method according to claim 1 or 4, wherein said estimation function is
    f(n)＝g(n)+h(n)f(n)=g(n)+h(n)
    其中，among them,
    f(n)为当前点到下一点的估计值，f(n) is the estimated value from the current point to the next point.
    g(n)为从起点s到节点n之间的实际值，代表了搜索广度的优先趋势，g(n) is the actual value from the starting point s to the node n, representing the priority trend of the search breadth.
    h(n)为从节点n到目标点D之间的最佳路径的估计值，包含了搜索中的启发信息。h(n) is an estimate of the best path from node n to target point D, containing heuristic information in the search.
  5. 根据权利要求1所述的方法，其特征在于，进一步包括：The method of claim 1 further comprising:
    使用超声波检测障碍物，并将障碍物在机器人坐标系下的位置转换为全局地图中的位置；Ultrasonic detection of obstacles and conversion of the position of the obstacle in the robot coordinate system to a position in the global map;
    设定障碍物检测阈值为1500mm，超过1500mm不做处理，小于1500mm则将障碍物在全局地图中标记。Set the obstacle detection threshold to 1500mm, do not process more than 1500mm, and mark obstacles in the global map if it is less than 1500mm.
  6. 根据权利要求1所述的方法，其特征在于，进一步包括： The method of claim 1 further comprising:
    规划出的路径用二维数组表示；The planned path is represented by a two-dimensional array;
    所述二维数组的行数表示路径中直线段的个数，列数表示每个直线段中的栅格位置；The number of rows of the two-dimensional array represents the number of straight segments in the path, and the number of columns represents the position of the grid in each straight segment;
    所述二维数组所定义的每行最后一个点为该段路径中的局部目标点。The last point of each row defined by the two-dimensional array is a local target point in the segment path.
  7. 根据权利要求1所述的方法，其特征在于，所述根据规划的路径控制机器人移动，进一步包括：The method according to claim 1, wherein the controlling the movement of the robot according to the planned path further comprises:
    在运动过程中实时更新机器人的位置和姿态；Updating the position and posture of the robot in real time during the movement;
    计算机器人当前位置与所述局部目标点的偏差，在行走过程中实时纠正偏差，实现机器人的实时控制。Calculate the deviation between the current position of the robot and the local target point, correct the deviation in real time during the walking process, and realize real-time control of the robot.
  8. 一种移动机器人避障导航的系统，其特征在于，包括控制单元、里程计、超声波传感器、姿态传感器，其中，A system for obstacle avoidance navigation of a mobile robot, comprising: a control unit, an odometer, an ultrasonic sensor, and an attitude sensor, wherein
    控制单元用于存储和调整地图，计算A*算法，控制机器人移动，纠正机器人移动的偏差；The control unit is used to store and adjust the map, calculate the A* algorithm, control the movement of the robot, and correct the deviation of the robot movement;
    里程计用于测量机器人在室内行走的距离；The odometer is used to measure the distance the robot walks indoors;
    超声波传感器用于探测机器人周围的障碍物信息；An ultrasonic sensor is used to detect obstacle information around the robot;
    姿态传感器用于探测机器人的姿态和移动方向。The attitude sensor is used to detect the attitude and direction of movement of the robot.
  9. 根据权利要求8所述的方法，其特征在于，进一步包括：The method of claim 8 further comprising:
    控制单元接收来自里程计的测量数据，计算机器人的位置；The control unit receives the measurement data from the odometer and calculates the position of the robot;
    控制单元根据机器人所处的位置，计算与规划路径中的局部目标点的偏差。The control unit calculates a deviation from the local target point in the planned path according to the position of the robot.
  10. 根据权利要求8所述的方法，其特征在于，进一步包括：The method of claim 8 further comprising:
    控制单元接收姿态传感器的测量数据，获得机器人的姿态和移动方向；The control unit receives the measurement data of the attitude sensor to obtain the posture and the moving direction of the robot;
    控制单元根据计算出的所述偏差和机器人的姿态，实时控制机器人的运动。 The control unit controls the motion of the robot in real time based on the calculated deviation and the posture of the robot.
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